Data Analysis & Statistics for Nursing Research; Denise F. Polit, Denise Polit-O'Hara; 1996

Data Analysis & Statistics for Nursing Research

av Denise F. Polit, Denise Polit-O'Hara
PLEASE PROVIDE COURSE INFORMATION

This introductory textbook uses a conversational style to teach students how to use statistical methods and procedures to analyze research findings. Students are guided through the complete analysis process from performing a statistical analysis to the rationale behind doing so. In addition, management of data, including how and why to recode variables for analysis, how to "clean" data, and how to work around missing data, is discussed.
PLEASE PROVIDE COURSE INFORMATION

This introductory textbook uses a conversational style to teach students how to use statistical methods and procedures to analyze research findings. Students are guided through the complete analysis process from performing a statistical analysis to the rationale behind doing so. In addition, management of data, including how and why to recode variables for analysis, how to "clean" data, and how to work around missing data, is discussed.
Utgiven: 1996
ISBN: 9780838563298
Förlag: PEARSON
Format: Bok
Språk: Engelska
Sidor: 506 st
PLEASE PROVIDE COURSE INFORMATION

This introductory textbook uses a conversational style to teach students how to use statistical methods and procedures to analyze research findings. Students are guided through the complete analysis process from performing a statistical analysis to the rationale behind doing so. In addition, management of data, including how and why to recode variables for analysis, how to "clean" data, and how to work around missing data, is discussed.
PLEASE PROVIDE COURSE INFORMATION

This introductory textbook uses a conversational style to teach students how to use statistical methods and procedures to analyze research findings. Students are guided through the complete analysis process from performing a statistical analysis to the rationale behind doing so. In addition, management of data, including how and why to recode variables for analysis, how to "clean" data, and how to work around missing data, is discussed.
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